Substance dispense evaluation system

ABSTRACT

An automated analysis instrument operates to detect inadequate dispensation of a fluidic substance on a tray. The instrument includes an image capturing device to capture an image of at least a portion of the tray including a receptacle portion and a surrounding portion around the receptacle portion. The instrument then identifies the surrounding portion of the at least the portion of the tray in the image, evaluates color components of the image corresponding to the surrounding portion of the at least the portion of the tray, and determines whether the fluidic substance is present on the surrounding portion of the at least the portion of the tray based on at least one of the color components.

This application is a continuation of U.S. application Ser. No.16/313,581 filed on Dec. 27, 2018, as a PCT International applicationand claims the benefit of priority to U.S. Provisional PatentApplication No. 62/357,096, filed on Jun. 30, 2016, titled SUBSTANCEDISPENSE EVALUATION SYSTEM, the disclosures of which is herebyincorporated by reference in its entirety.

BACKGROUND

Some biological sample analysis instruments utilize a system fordispensing fluidic substances, such as blood samples or other bodilyfluids, for analysis, as well as reagents or blood samples, foranalysis. For example, in a blood analysis system, reagents aredispensed on reaction wells of a tray. In some cases, the tray may notbe accurately aligned with reagent pipettors for various possiblereasons, and the reagent can be inadvertently dispensed onto the surfaceof the tray instead of into the reaction wells. Improper dispensation ofreagents may cause false results which are reported by the analysisinstrument in the same manner as true results. For example, in a bloodanalysis system, improper dispensation of reagents may result in a falsenegative agglutination pattern. False positive results may also resultfrom dispensing errors.

Several approaches have been used to attempt to detect improperdispensation of reagents. In certain examples, sensors are used todetect positions of dispensing probes relative to a tray at the time ofdispensation, or to monitor the inner pressure of probe tubing to detectdischarge of reagents or samples. In other examples, agglutinationpatterns are image-processed and evaluated. However, these approacheshave not been found to be adequate. For example, such approaches cannotcompletely separate true negative patterns from false negative patternsand/or true positive patterns from false positive patterns.

SUMMARY

In general terms, this disclosure is directed to a system for evaluatingfluidic substance dispensation. In one possible configuration and bynon-limiting example, the system employs photometric analysis of a trayon which a fluidic substance is dispensed. Various aspects are describedin this disclosure, which include, but are not limited to, the followingaspects.

One aspect is a method of evaluating dispensation of a fluidic substanceon a tray in an automated analysis instrument. The method includescapturing, using an image capturing device, an image of at least aportion of the tray, the at least a portion of the tray including areceptacle portion and a surrounding portion around the receptacleportion; identifying, using at least one computing device, thesurrounding portion of the at least the portion of the tray in theimage; evaluating color components of the image corresponding to thesurrounding portion of the at least the portion of the tray; anddetermining whether the fluidic substance is present on the surroundingportion of the at least the portion of the tray based on at least one ofthe color components.

Another aspect is a system for evaluating dispensation of a fluidicsubstance dispensed in an automated analyzer. The system includes a trayincluding a plurality of receptacles and a plurality of surroundingportions around the plurality of receptacles; a dispense deviceconfigured to dispense a fluidic substance on the tray; an imagecapturing device configured to capture at least one image of at least aportion of the tray; at least one processing device; at least onecomputer readable storage medium storing software instructions that,when executed by the at least one processing device, cause the systemto: capture an image of at least a portion of the tray, the at least aportion of the tray including a receptacle portion and a surroundingportion around the receptacle portion; identify the surrounding portionof the at least a portion of the tray in the image; evaluate colorcomponents of the image corresponding to the surrounding portion of theat least a portion of the tray; and determine whether the fluidicsubstance is present on the surrounding portion of the at least aportion of the tray based on at least one of the color components.

Yet another aspect is a computer-readable storage medium comprisingsoftware instructions that, when executed by at least one processingdevice of a substance dispensation evaluation system, cause thesubstance dispensation evaluation system in an automated analyzer to:obtain an image of at least a portion of a tray, the at least theportion of the tray including a receptacle portion and a surroundingportion around at least one open end of the receptacle portion; identifya first image portion of the image, the first image portioncorresponding to the surrounding portion of the at least the portion ofthe tray, the first image portion including a plurality of imagefragments; for each of the plurality of image fragments, obtain a valueassociated with a color of the image fragment; compare the value with afirst threshold; and designate the image fragment as a counted imagefragment if the value of the image fragment does not meet the firstthreshold; compare a number of the counted image fragments with a secondthreshold; and designate the at least the portion of the tray as aflagged tray if the number of the counted image fragments does not meetthe second threshold, the flagged tray representative of inappropriatedispensation of a fluidic substance to the at least the portion of thetray.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 schematically illustrates an example instrument for analyzing abiological sample.

FIG. 2 schematically illustrates another example of the instrument foranalyzing a biological sample.

FIG. 3 illustrates an exemplary architecture of a computing device thatcan be used to implement aspects of the present disclosure.

FIG. 4 schematically illustrates an example method of operating asubstance dispense system and a dispense evaluation system of thebiological sample analysis instrument of FIG. 1 .

FIG. 5 is a flowchart illustrating an example method of operating thedispense evaluation system.

FIG. 6 is a schematic top view of an example tray.

FIG. 7 is a cross sectional side view of the tray of FIG. 6 .

FIG. 8 is a flowchart illustrating an example method of operating thedispense evaluation system.

FIG. 9 illustrates an example image of a portion of a microplate.

FIG. 10 is a flowchart illustrating an example method of performingoperations of FIG. 8 .

FIG. 11 schematically illustrates a portion of the image of FIG. 9 .

FIG. 12 illustrates an example data set that includes color parametervalues representative of each image fragment.

FIG. 13 illustrates an example data set in which two color parametersare selected from three color parameters based on a type of fluidicsubstance.

FIG. 14 is a block diagram of an example comparison value calculator forgenerating a comparison value.

FIG. 15 is a flowchart illustrating an example method of operating thedispense evaluation system.

FIG. 16 illustrates example data associated with each image captured andanalyzed.

FIG. 17 is another example data associated with each image captured andanalyzed.

FIG. 18 is an example set of data generated as a result of dispensationevaluation.

FIG. 19 illustrates an example table of first and second thresholds.

FIG. 20 illustrates an example test result table that shows adequatedispensation based on the first and second thresholds shown in FIG. 19 .

FIG. 21 illustrates an example test result table that shows inadequatedispensation based on the first and second thresholds shown in FIG. 19 ,

FIG. 22 illustrates another example method of detecting inadequatedispensation of a fluidic substance on a tray.

DETAILED DESCRIPTION

Various embodiments will be described in detail with reference to thedrawings, wherein like reference numerals represent like parts andassemblies throughout the several views. Reference to variousembodiments does not limit the scope of the claims attached hereto.Additionally, any examples set forth in this specification are notintended to be limiting and merely set forth some of the many possibleembodiments for the appended claims.

FIG. 1 schematically illustrates an example instrument 100 for analyzinga biological sample. In some embodiments, the instrument 100 includes asubstance dispense system 102 and a substance dispense evaluation system104. A tray 108 is used to receive and contain a fluidic substance 110and is utilized by the systems 102 and 104 of the instrument 100. Insome embodiments, the instrument 100 is automated or semi-automated,wherein the tray 108 is used by the systems 102 and 104 independent of ahuman operator of the instrument, or with minimal intervention from anoperator.

In other embodiments, the instrument 100 further includes a substanceevaluation system 106. A tray 108 is used to receive and contain afluidic substance 110 and is utilized by the systems 102, 104, and 106of the instrument 100. In some embodiments, the instrument 100 isautomated or semi-automated, wherein the tray 108 is used by the systems102, 104, and 106 independent of a human operator of the instrument, orwith minimal intervention from an operator.

The biological sample analysis instrument 100 operates to analyze abiological sample for various purposes. In some embodiments, thebiological sample analysis instrument 100 includes a blood sampleanalysis instrument or apparatus. In some embodiments, the biologicalsample analysis instrument 100 operates to collect, test, process,store, and/or transfuse blood and its components, for example. The bloodcollection may occur at donor centers. The collected blood, and itscomponents, are then often processed, tested, and distributed at orthrough blood banks or clinical laboratories.

In the illustrated example, the instrument 100 is configured to performvarious types of blood tests, such as blood donor screening. Forexample, the instrument 100 offers automated simultaneous testing forABO/Rh including weak D, cytomegalovirus testing, and syphilisscreening. In some examples, the determination of an ABO Blood group isdefined by demonstrating the presence or absence of antigens A and/or Bon the surface of human red blood cells and detecting the presence orabsence of Anti-A and/or Anti-B antibodies in the plasma. As describedherein, the instrument 100 analyzes a biological sample (i.e., thefluidic substance 110), such as a mixture of a blood sample, a diluent,and/or a reagent, dispensed on the tray 108, such as a microplate havinga plurality of reaction wells.

The substance dispense system 102 operates to dispense a fluidicsubstance 110 on the tray 108. In some embodiments, the substancedispense system 102 includes one or more pipetting devices. A pipettingdevice may be fluidly connected to one or more bulk containers fordelivery of reagents, diluents and buffers, for example. Alternatively,a pipetting device operates to pipet fluidic substance from a samplecontainer into a well of tray 108. Such pipetting may be directed from asample tube to the tray 108, or may involve multiple pipetting steps,such as if an aliquot of sample is held in a secondary tube beforetransfer into tray 108. In the illustrated example of a blood sampleanalysis, the fluidic substance 110 can be any of a blood sample, adiluent, and a reagent, or any mixture thereof. The blood sampleincludes red blood cells and blood plasma. The reagent can be of varioustypes. Some examples of reagents include liquid reagents containingantibody, liquid reagents containing non-reactive ingredients, red bloodcells suspensions, and particle suspensions. Reagents have differentcolors. Some reagents can be colored to allow a user to distinguish thereagent from other substances. The colors of such reagents vary,including green, purple, yellow, blue, and red. Examples of the reagentinclude blood grouping reagents, such as Anti-A, Anti-B, Anti-A,B,Anti-D, Anti-C, Anti-E, Anti-c, Anti-e, and Anti-K reagents. The Anti-A,Anti-B, and Anti-A,B reagents are used in red blood cell determinationof the ABO blood group by determining the absence or presence oferythrocytic antigens A and/or B on the surface of human red bloodcells. The Anti-D reagents, such as Anti-D, Anti-D (PK1), and Anti-D(PK2), are used to determine the Rh type by detecting the presence ofthe D (Rh) antigen on the surface of human red blood cells. The Anti-C,Anti-E, Anti-c, Anti-e, and Anti-K are used for Rh-Kell phenotyping ofhuman red blood cells by detecting the presence of antigens C,E,c,e, andK on the surface of red blood cells. In other embodiments, the fluidicsubstance 110 can be of any types suitable for being dispensed on acontainer or tray and presented for further analysis.

The dispense evaluation system 104 operates to evaluate the dispensationof the fluidic substance 110. In particular, the dispense evaluationsystem 104 determines whether the fluidic substance 110 has beenappropriately dispensed on the tray 108 as intended for subsequentanalysis by, for example, the substance evaluation system 106. Aninappropriate dispensation of a fluidic substance on the tray 108 cancause a false result that may be indistinguishable from a true result,for example, or may otherwise compromise the operation of the biologicalsample analysis instrument 100.

The substance evaluation system 106 operates to evaluate the fluidicsubstance 110 that is contained on the tray 108. By way of example, thesubstance evaluation system 106 performs blood donor screening or bloodtransfusion inspection, which is described in more detail with referenceto FIG. 2 . Other types of analysis or evaluation can be performed bythe substance evaluation system 106 for various purposes. By way ofexamples, the substance evaluation system 106 may utilize any knownanalytic method and detection systems compatible with the tray 108 toanalyze a plurality of fluidic substances 110. Common examples includespectrophotometric detection and analysis to perform clinical chemistrytesting, immunoassays, microbiological identification and antibioticsusceptibility testing, and nucleic acid testing usingfluorescent-labeled primers and probes. Other analytical methodscompatible with semi-automated or automated sample handling on trays arealso known and compatible with the principles of the present disclosure.Some biological sample analysis instruments 100 may be user configurablefor selection of a substance evaluation system 106 suitable for avariety of research or diagnostic analysis.

The tray 108 is configured to receive the fluidic substance 110 from thesubstance dispense system 102 and hold the fluidic substance 110 forprocesses performed by the substance evaluation system 106. By way ofexamples, the tray 108 can be a multi-well plate, a microtiter plate, amulti-well panel, a multi-well cassette, a multi-well microfluidicdevice, a multi-well slide, a multi-well container, any holding devicewith multiple wells for receiving, holding, and/or reacting fluids, orany combination of the foregoing. An example of the tray 108 isillustrated and described with reference to FIGS. 4, 6, and 7 .

The fluidic substance 110 is dispensed on the tray 108 by the substancedispense system 102. In some embodiments, the fluidic substance 110 isthen examined by the substance evaluation system 106. The fluidicsubstance includes any substance that can be dispensed by the substancedispense system 102 and contained in the tray 108. In some embodiments,the fluidic substance 110 is a fluid of single substance. In otherembodiments, the fluidic substance 110 is a mixture of a plurality ofsubstances. In various embodiments, the fluidic substance 110 may be asample to be subjected to analysis, sample preparation components,diluents, buffers, reagents, or any combinations of the foregoing. Wherethe fluidic substance 110 involves blood or its components, examples ofthe fluidic substance 110 include whole blood, blood plasma, serum, redblood cells, white blood cells, platelets, diluents, reagents, or anycombinations thereof.

In the illustrated example of a blood sample analysis, the fluidicsubstance 110 can be any of a blood sample, a diluent, and a reagent, orany mixture thereof. The reagent can be of various types. Some examplesof reagents include liquid reagents containing labeled specific bindingreagents, for example antibody or nucleic acid probes, liquid reagentscontaining reactive and/or non-reactive ingredients, red blood cellssuspensions, and particle suspensions. Reagents may have differentcolors or produce different colors upon reaction. Some reagents can becolored to allow a user to distinguish the reagent from othersubstances. The colors of such reagents vary, including green, purple,yellow, blue, and red. Examples of the reagent include blood groupingreagents, such as Anti-A, Anti-B, Anti-A,B, Anti-D, Anti-C, Anti-E,Anti-c, Anti-e, and Anti-K, and Anti-k reagents. The Anti-A, Anti-B, andAnti-A,B reagents are used in red blood cell determination of the ABOblood group by determining the absence or presence of erythrocytic Aantigen and/or B antigen on the surface of human red blood cells. TheAnti-D reagents, such as Anti-D, Anti-D (PK1), and Anti-D (PK2), areused to determine the Rh type by detecting the presence of the D (Rh)antigen on the surface of human red blood cells. The Anti-C, Anti-E,Anti-c, Anti-e, Anti-K and Anti-k are used for Rh phenotyping and Kellphenotyping of human red blood cells by detecting the presence ofantigens C,E,c,e, and K and k on the surface of red blood cells. Inother embodiments, the fluidic substance 110 can be of any typessuitable for being dispensed on a container or tray and presented forfurther analysis. Furthermore, the fluidic substance can be other typesof bodily fluidic substances, such as saliva, cerebral spinal fluid,urine, amniotic fluid, urine, feces, mucus, cell or tissue extracts,nucleic acids, or any other type of bodily fluid, tissue or materialwhich is suspected of containing an analyte of interest.

In some embodiments, the fluidic substance 110 has a color differentfrom a color of the tray 108. In some embodiments, at least asurrounding portion 322 (FIG. 4 ) of the tray 108 has a color that isdistinguishable from the color of the fluidic substance 110.

With continued reference to FIG. 1 , in some embodiments, the instrument100 operates to communicate with a management system 112 via a datacommunication network 114. For example, the instrument 100 includes acommunication device (such as a communication device 246 in FIG. 3 )through which the instrument 100 communicates with the management system112.

In some embodiments, the management system 112 is remotely located fromthe instrument 100 and configured to perform diagnosis based on datafrom the instrument 100. In addition, the instrument 100 can evaluateperformance of the instrument and generate a report. One example of themanagement system 112 includes one or more computing devices executingPROSevice Remote Service Application available from Beckman Coulter,Inc., Brea, Calif.

The Beckman Coulter ProService Remote Service Application can provide asecure and continuous connection between the biological sample analysisinstrument 100 and a remote diagnosis command center (e.g., themanagement system 112) over a network (e.g., the network 114) using aRemote Application Processor (RAP) box. The RAP box can connect thebiological sample analysis instrument 100 to the remote diagnosiscommand center by way of the Internet via Ethernet port, Wi-Fi, orcellular network. The biological sample analysis instrument 100 can sendthe instrument data, such as instances of flagged trays, to the RAP box.The RAP box can then secures this data and forwards it to the remotediagnosis command center. All communications between the biologicalsample analysis instrument 100 and the remote diagnosis command centercan be coordinated through the RAP box. The RAP box can connect to thenetwork using a static or Dynamic Host Configuration Protocol (DHCP) IPaddress. The RAP box can be a hardware having computer processing boardsand connection ports capable of providing a secure transfer ofinstrument data from the biological sample analysis instrument 100 tothe remote diagnosis command center. For example, the RAP box can haveone or more Ethernet connection ports, one or more computer processingboards for Wi-Fi or cellular network connectivity, an electrical outletconnection port, or any combination of the foregoing.

The RAP box can have an internal firewall to provide a secure andcontinuous transfer of instrument data from the biological sampleanalysis instrument 100 and the remote diagnosis command center. Thisinternal firewall can create a private instrument network which isolatesthe biological sample analysis instrument 100 from other network trafficthat exists on the network. Furthermore, the RAP box can secure the datatransmission from the one or more analyzers to the biological sampleanalysis instrument 100 by the following one or more mechanisms. First,the outbound-initiated data messages are secured via encryption and sentthrough a firewall via HTTPS on Port 443, the standard port for secureInternet usage. Data is transmitted during Secure Sockets Layer (SSL),which is a protocol for transmitting information securely via theInternet. SSL creates a secure connection between a client and a server,over which data can be sent securely. Dual certification authenticationhelps prevent unauthorized access to transmitted data. An example of aSSL connection is the 128 bit AES, FIPS compliant encryption algorithm.Another mechanism that the RAP box can secure the data is using a RemoteDesktop Sharing (RDS) session. An RDS session is held through a secureVirtual Private Network (VPN) tunnel, which encapsulates the sessionbetween the biological sample analysis instrument 100 and the remotediagnosis command center to ensure no third-party interception of thedata being shared.

Still referring to FIG. 1 , the data communication network 114communicates digital data between one or more computing devices, such asbetween the data collection device 108 and the data processing system112. Examples of the network 114 include a local area network and a widearea network, such as the Internet. In some embodiments, the network 114includes a wireless communication system, a wired communication system,or a combination of wireless and wired communication systems. A wiredcommunication system can transmit data using electrical or opticalsignals in various possible embodiments. Wireless communication systemstypically transmit signals via electromagnetic waves, such as in theform of optical signals or radio frequency (RF) signals. A wirelesscommunication system typically includes an optical or RF transmitter fortransmitting optical or RF signals, and an optical or RF receiver forreceiving optical or RF signals. Examples of wireless communicationsystems include Wi-Fi communication devices (such as utilizing wirelessrouters or wireless access points), cellular communication devices (suchas utilizing one or more cellular base stations), and other wirelesscommunication devices.

FIG. 2 schematically illustrates another example of the instrument 100for analyzing a biological sample. As described in FIG. 1 , theinstrument 100 includes the substance dispense system 102, the dispenseevaluation system 104, and the substance evaluation system 106.

In the illustrated example, the biological sample analysis instrument100 is configured to analyze a blood sample. In some embodiments, thesubstance dispense system 102 includes a sample dispense system 120, adiluent dispense system 122, and a reagent dispense system 124.

The sample dispense system 120 operates to dispense a blood sample. Insome embodiments, the sample dispense system 120 includes a sample rackfeeder 130 that stores one or more sample racks 132. At least one of thesample racks 132 are selected and transferred to a location adjacent asample aspiration unit 134. The sample aspiration unit 134 includes asample pipettor 136 that aspirates a blood sample from the transferredsample rack, transfers the aspirated blood sample, and dispenses theblood sample to one or more reaction tubes 138. In some embodiments, thereaction tubes 138 containing the blood sample are transferred to thediluent dispense system 122. Alternatively, the diluent dispense system122 moves close to the reaction tubes 138 containing the blood sample.

The diluent dispense system 122 operates to dilute the sample. In someembodiments, the diluent dispense system 122 includes a diluent dispenseunit 142 and a diluted sample transfer unit 144. The diluent dispenseunit 142 operates to dispense a diluent into the reaction tubes 138containing the blood sample. The diluted sample transfer unit 144transfers the reaction tubes 138 containing a mixture of the bloodsample and the diluent to a tray 108. In some embodiments, the dilutedsample transfer unit 144 operates to aspirate the mixture of the bloodsample and the diluent from the reaction tubes 138 and dispense theaspirated substance on the tray 108.

The reagent dispense system 124 operates to dispense a reagent on thetray 108 containing the mixture of the blood sample and the diluent. Thereagent dispense system 124 includes a reagent transfer and dispenseunit 150. In some embodiments, the reagent transfer and dispense unit150 includes one or more reagent dispense pipettors 152. In someembodiments, the reagent transfer and dispense unit 150 moves to areagent supply 154 and aspirate a reagent therefrom via the dispensepipettors 152, and returns to the tray 108. Then, the reagent transferand dispense unit 150 is placed over the tray 108 such that the dispensepipettors 152 are aligned with the receptacle portions (e.g., reactionwells) of the tray 108. The reaction transfer and dispense unit 150operates to dispense the reagent on the tray 108 via the dispensepipettors 152.

Referring still to FIG. 2 , in some embodiments, the dispense evaluationsystem 104 includes an image capturing device 160 and an imageprocessing device 162.

When the fluidic substance 110 (e.g., a mixture of the blood sample, thediluent, and the reagent in the illustrated example) is dispensed on thetray 108, the tray 108 can be conveyed to the dispense evaluation system104. Alternatively, the dispense evaluation system 104 moves to the tray108.

The image capturing device 160 operates to capture an image of at leasta portion of the tray 108. In some embodiments, the image capturingdevice 160 includes a camera unit 164 and a light source 166. The cameraunit 164 includes a charge-coupled device (CCD) image sensor forobtaining a color digital image. The light source 166 is used toilluminate the tray 108 to be photographed as desired. The light source166 can be arranged in various locations. In the illustrated example,the light source 166 is positioned at the back of the tray 108 oppositeto the camera unit 164. Other locations of the light source 166 are alsopossible.

The image processing device 162 operates to process and evaluate theimage of the tray 108 captured by the image capturing device 160 todetermine if the fluidic substance 110 has been appropriately dispensedon the tray 108. In some embodiments, the image processing device 162includes at least some components illustrated in FIG. 3 . An exampleoperation of the image processing device 162 is described andillustrated with reference to FIGS. 4 and 5 .

FIG. 3 illustrates an exemplary architecture of a computing device thatcan be used to implement aspects of the present disclosure, includingthe biological sample analysis instrument 100 or various systems of theinstrument 100, such as the substance dispense system 102, the dispenseevaluation system 104, and the substance evaluation system 106. Further,one or more devices or units included the systems of the instrument 100can also be implemented with at least some components of the computingdevice as illustrated in FIG. 3 . Such a computing device is designatedherein as reference numeral 200. The computing device 200 is used toexecute the operating system, application programs, and software modules(including the software engines) described herein.

The computing device 200 includes, in some embodiments, at least oneprocessing device 202, such as a central processing unit (CPU). Avariety of processing devices are available from a variety ofmanufacturers, for example, Intel or Advanced Micro Devices. In thisexample, the computing device 200 also includes a system memory 204, anda system bus 206 that couples various system components including thesystem memory 204 to the processing device 202. The system bus 206 isone of any number of types of bus structures including a memory bus, ormemory controller; a peripheral bus; and a local bus using any of avariety of bus architectures.

Examples of computing devices suitable for the computing device 200include a desktop computer, a laptop computer, a tablet computer, amobile device (such as a smart phone, an iPod® mobile digital device, orother mobile devices), or other devices configured to process digitalinstructions.

The system memory 204 includes read only memory 208 and random accessmemory 210. A basic input/output system 212 containing the basicroutines that act to transfer information within computing device 200,such as during start up, is typically stored in the read only memory208.

The computing device 200 also includes a secondary storage device 214 insome embodiments, such as a hard disk drive, for storing digital data.The secondary storage device 214 is connected to the system bus 206 by asecondary storage interface 216. The secondary storage devices and theirassociated computer readable media provide nonvolatile storage ofcomputer readable instructions (including application programs andprogram modules), data structures, and other data for the computingdevice 200.

Although the exemplary environment described herein employs a hard diskdrive as a secondary storage device, other types of computer readablestorage media are used in other embodiments. Examples of these othertypes of computer readable storage media include magnetic cassettes,flash memory cards, digital video disks, Bernoulli cartridges, compactdisc read only memories, digital versatile disk read only memories,random access memories, or read only memories. Some embodiments includenon-transitory media.

A number of program modules can be stored in secondary storage device214 or memory 204, including an operating system 218, one or moreapplication programs 220, other program modules 222, and program data224.

In some embodiments, computing device 200 includes input devices toenable a user to provide inputs to the computing device 200. Examples ofinput devices 226 include a keyboard 228, pointer input device 230,microphone 232, and touch sensitive display 240. Other embodimentsinclude other input devices 226. The input devices are often connectedto the processing device 202 through an input/output interface 238 thatis coupled to the system bus 206. These input devices 226 can beconnected by any number of input/output interfaces, such as a parallelport, serial port, game port, or a universal serial bus. Wirelesscommunication between input devices and interface 238 is possible aswell, and includes infrared, BLUETOOTH® wireless technology, WiFitechnology (802.11a/b/g/n etc.), cellular, or other radio frequencycommunication systems in some possible embodiments.

In this example embodiment, a touch sensitive display device 240 is alsoconnected to the system bus 206 via an interface, such as a videoadapter 242. The touch sensitive display device 240 includes touchsensors for receiving input from a user when the user touches thedisplay. Such sensors can be capacitive sensors, pressure sensors, orother touch sensors. The sensors not only detect contact with thedisplay, but also the location of the contact and movement of thecontact over time. For example, a user can move a finger or stylusacross the screen to provide written inputs. The written inputs areevaluated and, in some embodiments, converted into text inputs.

In addition to the display device 240, the computing device 200 caninclude various other peripheral devices (not shown), such as speakersor a printer.

The computing device 200 further includes a communication device 246configured to establish communication across the network. In someembodiments, when used in a local area networking environment or a widearea networking environment (such as the Internet), the computing device200 is typically connected to the network through a network interface,such as a wireless network interface 248. Other possible embodiments useother wired and/or wireless communication devices. For example, someembodiments of the computing device 200 include an Ethernet networkinterface, or a modem for communicating across the network. In yet otherembodiments, the communication device 246 is capable of short-rangewireless communication. Short-range wireless communication is one-way ortwo-way short-range to medium-range wireless communication. Short-rangewireless communication can be established according to varioustechnologies and protocols. Examples of short-range wirelesscommunication include a radio frequency identification (RFID), a nearfield communication (NFC), a Bluetooth technology, and a Wi-Fitechnology.

The computing device 200 typically includes at least some form ofcomputer-readable media. Computer readable media includes any availablemedia that can be accessed by the computing device 200. By way ofexample, computer-readable media include computer readable storage mediaand computer readable communication media.

Computer readable storage media includes volatile and nonvolatile,removable and non-removable media implemented in any device configuredto store information such as computer readable instructions, datastructures, program modules or other data. Computer readable storagemedia includes, but is not limited to, random access memory, read onlymemory, electrically erasable programmable read only memory, flashmemory or other memory technology, compact disc read only memory,digital versatile disks or other optical storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or any other medium that can be used to store the desired informationand that can be accessed by the computing device 200.

Computer readable communication media typically embodies computerreadable instructions, data structures, program modules or other data ina modulated data signal such as a carrier wave or other transportmechanism and includes any information delivery media. The term“modulated data signal” refers to a signal that has one or more of itscharacteristics set or changed in such a manner as to encode informationin the signal. By way of example, computer readable communication mediaincludes wired media such as a wired network or direct-wired connection,and wireless media such as acoustic, radio frequency, infrared, andother wireless media. Combinations of any of the above are also includedwithin the scope of computer readable media.

Referring again to FIG. 3 , the computing device 200 can include alocation identification device 250. The location identification device250 is configured to identify the location or geolocation of thecomputing device 200. The location identification device 250 can usevarious types of geolocating or positioning systems, such asnetwork-based systems, handset-based systems, SIM-based systems, Wi-Fipositioning systems, and hybrid positioning systems. Network-basedsystems utilize service provider's network infrastructure, such as celltower triangulation. Handset-based systems typically use the GlobalPositioning System (GPS). Wi-Fi positioning systems can be used when GPSis inadequate due to various causes including multipath and signalblockage indoors. Hybrid positioning systems use a combination ofnetwork-based and handset-based technologies for location determination,such as Assisted GPS.

FIG. 4 schematically illustrates an example method 300 of operating thesubstance dispense system 102 and the dispense evaluation system 104 ofthe biological sample analysis instrument 100. An illustrative exampleof the tray 108 is also shown. The method 300 generally includesoperations 302 and 304.

At operation 302, the substance dispense system 102 operates to dispensea fluidic substance 110 on the tray 108. The substance dispense system102 includes a dispense device 310 having a dispense probe 312.

By way of example, the dispense device 310 can be configured as thereagent dispense system 124 (e.g., the reagent transfer and dispenseunit 150). In other examples, the sample dispense system 120 (e.g., thesample aspiration unit 134) or the diluent dispense system 122 (e.g.,the diluent dispense unit 142) is implemented as the dispense device310. In yet other examples, any other dispense devices suitable fordispensing or injection a fluidic substance can be used as the dispensedevice 310.

In some embodiments, the dispense probe 312 is a pipettor configured todispense the fluidic substance on the tray 108. By way of example, thedispense probe 312 can be the sample pipettor 136, a dispense tip fromthe diluent dispense unit 142, or the reagent dispense pipettor 152.

In some embodiments, the tray 108 includes a receptacle portion 320 anda surrounding portion 322. The receptacle portion 320 is a concaveportion formed on the tray 108 and configured to receive a fluidicsubstance from the dispense device 310. The surrounding portion 322 is aportion of the tray 108 that is arranged around the receptacle portion320 and not part of the receptacle portion 320. In some embodiments, thesurrounding portion 322 is a surface on the tray 108 around an openingof the receptacle portion 320.

The substance dispense system 102 (e.g., the dispense device 310) isconfigured to ideally dispense the fluidic substance 110 only into thereceptacle portion 320 of the tray 108 and not on the surroundingportion 322 or any other portion of the tray 108. However, the fluidicsubstance 110 can be injected or dispensed not only into the receptacleportion 320 but on the surrounding portion 322 due to various reasons.In some cases, misalignment of the dispense device 310 relative to thetray 108, and malfunction or mishandling of the system, can cause aninappropriate dispensation or spillover of the fluidic substance on thetray 108. For example, when a fluidic substance is dispensed into thereceptacle portion 320 of the tray 108, the tray 108 is not properlyaligned with the dispense probe 312. As a result, the dispense probe 312can miss the receptacle portion 320 and dispense at least some of thefluidic substance onto the surrounding portion 322 of the tray 108. Suchimproper dispensing of the fluidic substance to the tray 108 can causeinaccurate, unreliable results at subsequent evaluation processes, suchas at the substance evaluation system 106. In the illustrated example ofFIG. 2 , in which a blood transfusion inspection is performed, thesubstance evaluation system 106 cannot distinguish between a falsenegative agglutination pattern due to improper dispense on the tray 108from a true negative agglutination pattern. As such, the verificationthat the fluidic substance has been properly dispensed on the tray isimportant to eliminate such false results.

Once the fluidic substance 110 is dispensed to the tray 108 by thesubstance dispense system 102 (at the operation 302), the tray 108 isevaluated using the dispense evaluation system 104 at operation 304. Insome embodiments, the tray 108 is conveyed to the dispense evaluationsystem 104. In other embodiments, the tray 108 remains stationary whilethe dispense evaluation system 104 replaces the substance dispensesystem 102. The dispense evaluation system 104 can come close to thetray 108 after the substance dispense system 102 moves away from thetray 108. Alternatively, the dispense evaluation system 104 isintegrally configured with the substance dispense system 102 so that theoperations 302 and 304 are sequentially performed while the tray 108 isstationary.

As described above, the dispense evaluation system 104 includes theimage capturing device 160 and the image processing device 162. Anexample of the operation 304 is described in more detail with referenceto FIG. 5 .

FIG. 5 is a flowchart illustrating an example method 350 of operatingthe dispense evaluation system 104 (i.e., the operation 304 in FIG. 4 ).In some embodiments, the method 350 includes operations 352, 354, and356. In some embodiments, the method 350 includes operations that areperformed by the dispense evaluation system 104. For example, theoperations in the method 350 are executed by one or more processors,such as the processing device 202 as illustrated in FIG. 3 . Although itis primarily illustrated herein that the dispense evaluation system 104performs the operations of the method 350, at least one of theoperations in the method 350 can be performed by other systems orcomponents of the instrument 100, independently from or in cooperationwith the dispense evaluation system 104.

At operation 352, the dispense evaluation system 104 operates to capturean image of the tray 108, on which the fluidic substance 110 has beendispensed as in the operation 302 of FIG. 4 . In some embodiments, theimage capturing device 160 is placed over the tray 108 and takes animage 330 (FIGS. 4 and 9 ) of at least a portion of the tray 108 suchthat the receptacle portion 320 and the surrounding portion 322 aroundthe receptacle portion 320 are included in the image 330.

At operation 354, the dispense evaluation system 104 operates to analyzethe image 330. In some embodiments, the image processing device 162operates to process the image 330 and generate one or more parametersthat can be used to evaluate the dispensing of the fluidic substance onthe tray 108. An example of the operation 354 is described andillustrated with reference to FIG. 8 .

At operation 356, the dispense evaluation system 104 operates toevaluate the appropriateness of the substance injection. In someembodiments, the image processing device 162 uses the parametersgenerated by analyzing the image 330 and determines if the fluidicsubstance has been properly dispensed on the tray 108. An example of theoperation 456 is described and illustrated with reference to FIG. 8 .

With reference to FIGS. 6 and 7 , an example of the tray 108 isdescribed. In particular, FIG. 6 is a schematic top view of an exampletray 108, and FIG. 7 is a cross sectional side view of the tray 108 ofFIG. 6 .

In the illustrated example, the tray 108 is configured as a microplate370. The microplate 370 includes a plurality of wells 372 that providereaction vessels to analyze components of a fluidic substance (e.g., aspecimen). The wells 372 have circular openings that are formed on adispensation surface 374 of the microplate 370, and a surroundingportion or surface 376 is defined as the dispensation surface 374surrounding the openings of the wells 372. In some embodiments, thewells 372 are formed in a substantially concave shape and arranged inmatrix on the dispensation surface 374 of the microplate 370. As such,the wells 372 of the microplate 370 correspond to the receptacle portion320 of the tray 108, and the surrounding surface 376 of the microplate370 corresponds to the surrounding portion 322 of the tray 108. In someembodiments, the microplate 370 is formed by injection molding syntheticresin such as acrylic.

In some embodiments, each well 372 of the microplate 370 is configuredto receive a specimen to be tested and a reaction reagent that causes anantigen-antibody reaction with the specimen. After a predetermined timefrom this dispensation, at least a portion of the microplate 370 withthe reaction caused in the wells 372 is imaged by the image capturingdevice 160 and the dispensation is analyzed with the captured image asdescribed herein.

As illustrated in FIG. 7 , any cross-section (a horizontal cross-sectionas taken along line A-A) that is parallel to the opening plane (i.e.,the dispensation surface 374) of the well 372 is circle, and a diameterof the circle on each horizontal cross-section becomes smaller graduallytoward a bottom from the opening plane. In particular, a bottom 378serving as a liquid containing basin at the time of dispensation is in asubstantially circular conic shape. In some embodiments, an includedportion in the bottom 378 has such a configuration that a diameterthereof changes slightly stepwise to increase surface area thereof sothat precipitation of a reactant condensed as a result of anantigen-antibody reaction is facilitated.

By way of example, when a specimen, such as blood and body fluid, and areagent including a substance that causes a specific reaction with acertain substance in the specimen, are respectively dispensed for anappropriate amount in the wells 372 of the microplate 370, thesubstances causes an antigen-antibody reaction inside the wells 372 ofthe microplate 370. For example, when blood typing is performed usingred corpuscles in blood, the red corpuscles causes an antigen-antibodyreaction with a certain antibody included in a reagent to beagglutinated. The agglutinated red corpuscles precipitate at theinclined portion in steps of the bottom 378. The agglutination patternformed by the precipitation differs depending on a blood type, andtherefore, by analyzing image data that is obtained by imaging theagglutination pattern by an appropriate imaging means, the blood type ofthe specimen is determined. Because the agglutination pattern obtainedby the antigen-antibody reaction appears at the inclination portion ofthe bottom 378 of the well 372, to image this condensation pattern, itis required to take the focus position of the imaging means near thebottom 378.

Referring to FIGS. 8 and 9 , an example method 400 of operating thedispense evaluation system 104 is described in more detail. FIG. 8 is aflowchart illustrating an example method 400 of operating the dispenseevaluation system 104. The method 400 is described with also referenceto FIG. 9 , which illustrates an example image 330 of a portion of themicroplate 370.

The method 400 includes operations that can be executed by the imageprocessing device 162 of the dispense evaluation system 104. In someembodiments, the operation 354 as described in FIG. 5 is implemented inthe method 400. In the illustrated embodiment, the method 400 includesoperations 402, 404, and 406.

The method 400 is performed once an image 330 of at least a portion ofthe tray 108 is captured by the image capturing device 160. Prior to themethod 400, the tray 108 is imaged by the image capturing device 160 asillustrated in FIG. 4 (e.g., the operation 352 as shown in FIG. 5 ). Theimage capturing device 160 can capture an image 330 of at least aportion of the tray 108 such that the image 330 includes one or morereceptacle portion 320 and a surrounding portion 322 around thereceptacle portions 320.

In the present disclosure, the method 400 is primarily described withthe microplate 370 as the tray 108, which includes a plurality ofreceptacle portions 320 (e.g., a plurality of wells 372) and a pluralityof surrounding portions 322 (e.g., a plurality of surrounding portions376). In the illustrated embodiment, the image capturing device 160operates to take an image 330 of a portion of the tray 108 such that theimage includes only one receptacle portion 320 (e.g., a single well 372)and a surrounding portion 322 (e.g., a single surrounding portion 376)around the receptacle portion 320. To evaluate the entire tray 108 inthis configuration, a plurality of images are taken for differentportions of the tray 108 such that the plurality of images incombination can represent the entire tray 108 (e.g., the microplate370). As described herein, each of the images can be processed andanalyzed for evaluating the appropriateness of dispensation of a fluidicsubstance.

In other embodiments, the image capturing device 160 captures an imageof a portion of the tray 108 such that the image includes two or morereceptacle portions and surrounding portions associated with thereceptacle portions. In this configuration, the image capturing device160 needs to capture a plurality of such images if the entire tray 108is to be evaluated.

Alternatively, the tray 108 (e.g., the microplate 370) can be imaged indifferent manners for executing the method 400. Where the tray 108includes a single receptacle portion 320 and a surrounding portion 322around the receptacle portion 320, the image 330 is captured to includethe receptacle portion 320 and at least a part of the surroundingportion 322. Where the tray 108 includes a plurality of receptacleportions 320 and a plurality of surrounding portions 322 (e.g., wherethe tray 108 is a microplate 370), the image capturing device 160 cancapture an image of the entire tray 108 at once so that the imageincludes the plurality of receptacle portions and the plurality ofsurrounding portions. In subsequent processes, the image of the entiretray can be divided into a plurality of pieces (also referred to hereinas sub-images), each of which is subjected to image evaluation asdescribed herein. Each piece of the image can include at least one ofthe receptacle portions and at least one of the surrounding portionsthat is around the one of the receptacle portions. In other embodiments,each piece of the image can include two or more of the receptacleportions and two or more of the surrounding portions that are around thetwo or more of the receptacle portions.

In yet other embodiments, a predetermined region of the tray 108 isimaged and evaluated to determine the appropriateness of dispensationfor the entire tray 108 or for that region of the tray 108.

Referring still to FIG. 8 , at operation 402, the image processingdevice 162 identifies the surrounding portion 322 around the receptacleportion 320 of the tray 108 in the image 330. The image 330 can beanalyzed using various image processing techniques to identify a portionof the image 330 that corresponds to the surrounding portion 322 of thetray 108. In the illustrated example of FIG. 9 , the image 330represents a portion of the microplate 370 that includes one well 372and a surrounding portion 376 around the well 372. In some embodiments,a surrounding image portion 430 of the image 330 that corresponds to thesurrounding portion 376 around the well 372 can be identified using edgedetection, in which a boundary of the well 372 is found in the image330. For example, discontinuities in brightness can be detected in theimage 330 to find the boundary of the well 372. Other techniques can beused to identify the surrounding image portion 430 of the image 330,which corresponds to the surrounding portion 376 around the well 372.

At operation 404, the image processing device 162 evaluates colorcomponents of the surrounding image portion 430 of the image 330. Suchcolor components can be obtained from signals outputted the imagecapturing device 160. The color components can be associated differentcolor components depending on different color models. For example, inthe RGB color model, the color components include red, green, and bluecomponents. In the CMYK color model, the color components include cyan,magenta, yellow, and black. Other combinations of color components arealso possible in other embodiments. An example of the operation 404 isdescribed in more detail with reference to FIG. 10 .

At operation 406, the image processing device 162 determines whether thefluidic substance 110 is present on the surrounding portion 376 aroundthe well 372 of the microplate 370. In some embodiments, thedetermination is made based on at least one of the color components ofthe surrounding image portion 430 of the image 330. An example of theoperation 404 is described in more detail with reference to FIG. 10 .

FIG. 10 is a flowchart illustrating an example method 450 of performingsome of the operations in the method 400 of FIG. 8 . The method 450 isdescribed with further reference to FIG. 11 , which schematicallyillustrates a portion of the image 330 of FIG. 9 . In some embodiments,an example method 450 implements the operations 404 and 406. The method450 can include operations 452, 454, 456, and 458.

At operation 452, the image processing device 162 identifies a pluralityof image fragments 470 in the surrounding image portion 430 of the image330. As illustrated in FIG. 11 , the surrounding image portion 430 ofthe image 330 can be divided into a plurality of image fragments 470 forsubsequent analysis. In some embodiments, the image fragments 470correspond to pixels of the image 330. The image fragments 470 can beidentified in various manners. In some embodiments, the image fragments470 are numbered for identification. In the illustrated embodiment ofFIG. 11 , one of the image fragments is identified by a serial number“564” and another image fragment is identified by a serial number “754.”

At operation 454, the image processing device 162 obtains colorparameters 472 for each of the image fragments 470. In the illustratedembodiment, three color parameters (i.e., first, second, and third colorparameters 474, 476, and 478 in FIG. 11 ) are obtained for each imagefragment 470. The color parameters are measured by various manners. Insome embodiments, the values of color components are be scaled, forexample from 0 to 99. By way of example, in FIG. 11 , the image fragmentidentified by “564” has a first color parameter value of 30, a secondparameter value of 79, and a third parameter value of 3, and the imagefragment identified by “754” has a first color parameter value of 45, asecond parameter value of 65, and a third parameter value of 2.

In some embodiments, the three color parameters 474, 476, and 478 aredetermined from color components based on various color models. Forexample, the color parameters 474, 476, and 478 are the values of red,green, and blue components in the RGB color model. Other types andnumbers of color parameters can be obtained in other embodiments. Forexample, in the CMYK color model, four color components, such as cyan,magenta, yellow, and black components, can be used. An example set ofcolor parameter data for color fragments is illustrated in FIG. 12 .

At operation 456, the image processing device 162 selects one or more ofthe color parameters 472 based on the type of the fluidic substance 110dispensed on the tray 108. In the illustrated embodiments, two colorparameters are selected from the three color parameters 472 depending onthe characteristics of the fluidic substance 110. An example selectionof color parameters (i.e., a parameter selection 494) is illustrated inFIG. 13 .

At operation 458, the image processing device 162 calculates acomparison value 502 (FIG. 14 ) based on the selected color parametersfor each of the image fragments 470. Some examples of the comparisonvalue 502 are described and illustrated in more detail with reference toFIG. 14 .

FIG. 12 illustrates an example data set 480 that includes the values ofthe color parameters 472 representative of each image fragment 470. Byway of example, the first, second, and third color parameters 474, 476,and 478 are the values of red, green, and blue components in each pixelwithin the surrounding image portion 430 of the image 330. In theillustrated embodiments, the surrounding image portion 430 of the image330 includes 130,569 pixels, each of which has the values of threedifferent color parameters.

FIG. 13 illustrates an example data set 490 in which two colorparameters (e.g., a parameter selection 494) are selected from the threecolor parameters based on the type of fluidic substance dispensed on thetray 108. In the illustrated example where a blood sample is tested, thesubstance type 492 can be determined by either or both of the bloodsample type and the reagent type.

In some embodiments, the color parameters 472 are selected such that oneof the selected color parameters closely matches the color of thefluidic substance and the other color parameter is different from thecolor of the fluidic substance. In the illustrated example of FIG. 13 ,when the fluidic substance is a mixture of red blood cells and the firsttype of reagent (“Reagent 1”), the first and second color parameters 474and 476 are selected for dispensation evaluation. One of the first andsecond color parameters 474 and 476 can be selected so as to match thecolor of the mixture of red blood cells and Reagent 1 as closely aspossible, and the other color parameter has a color that is as differentas possible. For example, the other color parameter can be selected tobe complementary to the color of the fluid substance. By way of example,where the RGB color model is used to analyze the image 330, a red colorparameter is selected as a first color parameter when red blood cellsare used as a blood sample (because the color of red blood cells isred), and either a green color parameter or a blue color parameter canbe chosen as a second color parameter. When a blood sample is bloodplasma, which is substantially yellow, a green color parameter can beused as a first color parameter that closely matches the color of theblood sample, and either a red color parameter or a blue color parametercan be selected as a second color parameter that is far from the colorof the blood sample. In other examples, the color of a reagent used canbe referred to in selecting the color parameters. For examples, wherethe reagent is green, a green color parameter is used as a first colorparameter, and either a red color parameter or a blue color parameter isselected as a second color parameter.

FIG. 14 is a block diagram of an example comparison value calculator 500for generating a comparison value 502. In some embodiments, thecomparison value calculator 500 receives the color parameters (i.e., theselected color parameters 494) selected based on the type of fluidicsubstance dispensed on the tray 108, and generates a comparison value502 suitable for evaluating the substance dispensation on the tray 108.

The comparison value 502 is a function of the selected color parameters494. In the illustrated embodiment, two color parameters, such as thefirst and second color parameters 494A and 494B, are used as variablesfor the comparison value 502. In some embodiments, the comparison value502 includes a ratio 504 between the first and second color parameters494A and 494B. In other embodiments, the comparison value 502 includes adifference 506 between the first and second color parameters 494A and494B. In yet other embodiments, the comparison value 502 includes othervalues associated with the selected color parameters 494.

FIG. 15 is a flowchart illustrating an example method 530 of operatingthe dispense evaluation system 104. In particular, the method 530includes operations that can be executed by the image processing device162 of the dispense evaluation system 104. In some embodiments, theoperation 356 as described in FIG. 5 is implemented in the method 530.In the illustrated embodiment, the method 530 includes operations 532,534, 536, 538, 540, 542, and 544. The method 530 is described withfurther reference to FIGS. 16 and 17 .

At operation 532, the image processing device 162 compares thecomparison value 520 with a first threshold 552 for each image fragment470. The first threshold 552 provides a reference value for evaluatingthe image fragments 470.

Referring again to FIG. 13 , a plurality of first thresholds 552 areprovided. The first threshold 552 varies in accordance with the type ofsubstance dispensed on the tray 108. In some embodiments, a set of firstthresholds 552 are experimentally determined so as to improve theaccuracy and reliability in the substance dispensation evaluationresult. Further, the first threshold 552 is provided differently for thetype of comparison value 502. For example, the first threshold 552A isadapted for the ratio comparison value 504, and the first threshold 552Bis provided for the difference comparison value 506. One example set offirst thresholds is described with reference to FIG. 19 .

Referring back to FIG. 15 , at operation 534, the image processingdevice 162 determines the number of image fragments 470 that do notsatisfy the first threshold 552. For each image fragment 470, it isdetermined whether the comparison value 502 does not satisfy the firstthreshold 552. If the comparison value 502 for a particular imagefragment does not meet the first threshold 552, that image fragment canbe designated as a counted image fragment. Once such determination ismade for all of the image fragments under evaluation, the total numberof the image fragments 470 not satisfying the first threshold 552 isobtained for the entire image fragments 470 subjected to thedispensation evaluation. In the present disclosure, the total number ofsuch unsatisfactory image fragments can be referred to as a total numberof counted image fragments. In some embodiments, only a portion of theentire image fragments 470 are analyzed to generate the total number ofcounted image fragments.

In some embodiments, the comparison value 502 does not meet the firstthreshold 552 if the comparison value 502 exceeds the first threshold552 (e.g., in FIG. 17 ). In other embodiments, the comparison value 502does not satisfy the first threshold 552 if the comparison value 502 issmaller than the first threshold 552 (e.g., in FIG. 16 ).

At operation 536, the image processing device 162 compares the totalnumber of counted image fragments with a second threshold 554. Thesecond threshold 554 provides a reference value for determining if therehas been a spillover of the fluidic substance dispensed on the tray 108.In the present disclosure, the second threshold 554 can be referred toas a cutoff value. As described below, if the number of image fragmentsthat do not meet the first threshold 552 exceeds the cutoff value, it isconsidered that the fluidic substance has spilled on the surroundingportion around the receptacle portion of the tray. One example set ofsecond thresholds is described with reference to FIG. 19 .

At operation 538, the image processing device 162 determines whether thetotal number of counted image fragments satisfies the second threshold554. In some embodiments, the total number of counted image fragmentsmeets the second threshold 554 if the total number of counted imagefragments is smaller than the second threshold 554. In otherembodiments, the total number of counted image fragments meets thesecond threshold 554 if the total number of counted image fragments isnot greater than the second threshold 554.

If it is determined that the total number of counted image fragmentssatisfies the second threshold 554 (“YES” at the operation 538), themethod 530 moves on to operation 540. Otherwise (“NO” at the operation538), the method 530 continues to operation 544.

At operation 540, the image processing device 162 determines whetherthere are any image fragments 470 that have not been evaluated throughthe operations 532, 534, 536, and 538. If any image fragment 470 isfound unexamined (“YES” at the operation 540), the method 530 returns tothe operation 532 and the subsequent operations that are performed forthe unexamined image fragments. If there is no image fragment 470unexamined (“NO” at the operation 540), the method 530 continues tooperation 542.

At operation 542, the image processing device 162 recognizes that thefluidic substance has been appropriately dispensed on the tray 108. Insome embodiments, the image processing device 162 operates to storeinformation representative of such appropriate dispensation. Forexample, the image processing device 162 can update data associated withthe tray 108 to include information that the fluidic substance has beenproperly dispensed on the tray 108 for further analysis. In otherembodiments, the image processing device 162 terminates the dispensationevaluation process without performing any other operation. This canindicate the appropriateness of dispensation as opposed to flagging atthe operation 544.

At operation 544, the image processing device 162 operates to designatethe tray 108 as flagged. In some embodiments, the image processingdevice 162 stores a flag indicative of inappropriate dispensation of thefluidic substance on the tray 108. The flag associated with the tray 108represents an inappropriate dispensation of the fluidic substance on thetray 108.

FIG. 16 illustrates example data 550 associated with each image 330captured and analyzed as described herein. In some embodiments, the data550 represent the image fragment analysis for an image of at least aportion of the tray, as shown in some of the operations of FIG. 15 . Inthe illustrate example, the image was captured for each well 372 of themicroplate 370, and a plurality of image fragments 470 of the image,which represent a surrounding portion 376 around that well 372 withinthe image, are evaluated.

In some embodiments, the data 550 includes a well ID 556 to identify thewell 372 of the microplate 370, which has been analyzed to dispensationevaluation. The data 550 can include various pieces of information thatare associated with the analysis, such as the type of substancedispensed on the microplate (i.e., the substance type 492), the colorparameters 494 used for analysis, the comparison value 502 used foranalysis, the first threshold 552 used for analysis, and the secondthreshold 554 used for analysis.

As illustrated, the data 550 can identify the plurality of imagefragments within the image by image fragment IDs 558. For each imagefragment 470, the comparison value 502 is calculated based on the typeof comparison value defined for the analysis. In the illustratedexample, the ratio comparison value 504 is used and defined as a ratioof the second color parameter over the third color parameter. The ratiocomparison value 504 is calculated for each image fragment 470 andassociated with an image fragment ID 558 for that image fragment 470.The data 550 further include information as to whether the ratiocomparison value 504 exceeds the first threshold 552. Moreover, the data550 include the total number of image fragments that do not satisfy thefirst threshold (i.e., the total number of counted image fragments 560).In this case, the image fragments having comparison values that do notexceed the first threshold are counted into the total number of countedimage fragments 560.

In some embodiments, the data 550 further include information as towhether the total number of counted image fragments 560 exceeds thesecond threshold 554. In the illustrated example, the total number ofcounted image fragments 560 (e.g., 53 in FIG. 16 ) exceeds the secondthreshold 554 (e.g., 50 in FIG. 16 ). In this case, the well 372 of themicroplate 370 associated with the data 550 can be flagged to indicatean inappropriate dispensation of the fluidic substance on the well 372.

FIG. 17 is another example data 570 associated with each image 330captured and analyzed as described herein. The data 570 are similar tothe data 550 of FIG. 17 except for the type of comparison value 502 usedfor analysis.

In some embodiments, the data 570 represent the image fragment analysisfor an image of at least a portion of the tray, as shown in some of theoperations of FIG. 15 . In the illustrate example, the image wascaptured for each well 372 of the microplate 370, and a plurality ofimage fragments 470 of the image, which represent a surrounding portion376 around that well 372 within the image, are evaluated.

Similarly to the data 550, the data 570 can include information aboutthe well ID 556, the substance type 492), the color parameters 494 usedfor analysis, the comparison value 502 used for analysis, the firstthreshold 552 used for analysis, and the second threshold 554 used foranalysis.

As illustrated, the data 570 can identify the plurality of imagefragments within the image by image fragment IDs 558. For each imagefragment 470, the comparison value 502 is calculated based on the typeof comparison value defined for the analysis. In the illustratedexample, the difference comparison value 506 is used and defined as thedifference between the second color parameter and the third colorparameter. The difference comparison value 506 is calculated for eachimage fragment 470 and associated with an image fragment ID 558 for thatimage fragment 470. The data 570 further include information as towhether the difference comparison value 506 is smaller than the firstthreshold 552. Moreover, the data 570 include the total number of imagefragments that do not satisfy the first threshold (i.e., the totalnumber of counted image fragments 560). In this case, the imagefragments having comparison values that are equal to or exceed the firstthreshold are counted into the total number of counted image fragments560.

In some embodiments, the data 570 further include information as towhether the total number of counted image fragments 560 exceeds thesecond threshold 554. In the illustrated example, the total number ofcounted image fragments 560 exceeds the second threshold 554. In thiscase, the well 372 of the microplate 370 associated with the data 570can be flagged to indicate an inappropriate dispensation of the fluidicsubstance on the well 372.

FIG. 18 is an example set of data 600 that is generated as a result ofthe dispensation evaluation for a tray 108. In the illustrated example,the tray 108 is a microplate 370 including a plurality of wells 372. Insome embodiments, the data 600 include a microplate ID 602, which isused to identify the microplate 370 on which the fluidic substance hasbeen dispensed. The data 600 can further include information about thenumber of wells included in the microplate (i.e., the number of wells604), a dispensation date 606, the type of substance dispensed on themicroplate (i.e., the substance type 492), the color parameters 494 usedfor analysis, the comparison value 502 used for analysis, the firstthreshold 552 used for analysis, and the second threshold 554 used foranalysis. Further, the data 600 includes a flag status 608. In otherembodiments, other pieces of information are included in the data 600.

As illustrated, the data 600 include information 612 as to whether thesecond threshold 554 was satisfied for each well 372. As describedabove, the well 372 that does not meet the second threshold 554 can beflagged as indicating an inappropriate dispensation on that well 372.Such information 614 is also included in the data 600, as illustrated inthe third column of the table.

The appropriateness of dispensation on the microplate 370 as a whole isdetermined based on the flagging results of the wells 372 of themicroplate 370. The microplate 370 is flagged to indicate that thefluidic substance has not been properly dispensed on the microplate 370and, thus, is not ready for further analysis. The flag status 608 isused to indicate whether the microplate 370 is flagged or not. In someembodiments, the microplate 370 is determined as flagged if any of thewells 372 is flagged. In other embodiments, the microplate 370 isregarded as flagged if a predetermined number of the wells 372 areflagged.

The flag status 608 is presented to a user of the instrument 100 invarious manners. In some embodiments, the flag status 608 is displayedon a screen provided on the instrument 100 to inform the user of theappropriateness of dispensation (and thus the readiness for furtheranalysis). In other embodiments, the flag status 608 is included in areport that can be displayed or printed out for the user. In yet otherembodiments, at least part of the data 600 is displayed or printed outfor the user's reference.

As described herein, in an exemplary embodiment of the presentdisclosure, the CCD camera takes a color digital image of each well onthe microplate. For example, when the microplate has 120 wells, 120color images can be captured for individual evaluation. The CCD cameraoutputs three separate signals for each pixel, which correspond to theprimary colors, such as red, green, and blue in the RGB color model. Oneach color image, the top surface of the microplate, which can bereferred to herein as the outside-of-well region, is identified basedon, for example, edge detection process. The outside-of-well region isanalyzed for photometric values to determine if the colored fluidicsubstance (e.g., reagent or sample) are dispensed onto the surface ofthe microplate. In the meantime, two of the three primary colors areselected based on the dispensed fluidic substance type. Then, for eachpixel, the difference and/or the ratio of the two primary colors arecalculated. The calculated difference or ratio is compared to a firstreference value. This first reference value can vary depending on thetype of fluidic substance. The computer console can store one or morefirst reference values for each fluidic substance that is registered onthe computer console to be used on the instrument 100. By way ofexample, the computer console for this system holds 99 or more of firstreference values for reagents and sample types used on the instrument.For each pixel, if the calculated difference or ratio does not meet thefirst reference value (e.g., the calculated difference or ratio is aboveor below the first reference value), then a value of one pixel is addedto the total counted pixels. By way of example, each color image has313,600 pixels total for a 560×560 digital image, so the outside-of-wellregion would roughly account for about 100,000 pixels total. Finally,the total counted pixels is compared to a second reference value. Thesecond reference value is a threshold cut-off value. If the totalcounted pixels is greater than the second reference value, then animproper reagent dispense is flagged. Even if one well is flagged, theentire result for the microplate can be flagged. Although it isillustrated that the wells of the microplate are separately evaluatedone by one, it is also possible to evaluate the appropriateness ofdispensation based on two or more wells of the microplate, based on aparticular region of the microplate, or based on the entire microplate.

As discussed herein, a fluidic substance (e.g., colored reagents and/orblood samples) to be dispensed on a microplate is colored. Thus, ifthere is no spillover or improper dispensation between wells of themicroplate, an image of the surface between the wells shows the originalcolor of the surface (or the original color of the microplate if themicroplate is formed in the same color). If the fluidic substance ismis-dispensed on the microplate, the color of a least a portion of thesurface between the wells of the microplate appears differently from theoriginal color of the surface of the microplate. The system as describedherein automatically captures and processes the image, and evaluates thedispensation of the fluidic substance on the microplate based on thecolor parameters from the image.

Referring to FIGS. 19-21 , an example set of first and secondthresholds, and example test results based on the thresholds, aredescribed. In this example, the first threshold 552 is determined to bearound the maximum value among images with adequate dispensation, andthe second threshold 554 is set to correspond around 1% of the number ofpixels on the outside well region. In this example, each captured imagehas a resolution of 560×560 and thus has 313,600 pixels. The well regionhas a circular top portion having a radius of 165 pixels, and thus has asize of about 85,530 pixels. The outside well region has a size of about228,070 pixels (=313,600−85,530 pixels). It is noted that the first andsecond thresholds, the image, the well region, and/or the outside wellregion can be determined and designed differently in other examples.

In this example, different reagents are considered. One example type ofreagents includes Diagast reagents that are commercialized by BeckmanCoulter, Inc. Another example type of reagents includes Wako reagentsavailable from Wako Pure Chemical Industries. Ltd. The colors of anti-A(blue) and anti-B (yellow) are specified by WHO. It is noted that typeof dye and concentration are different among different manufacturers. Inother examples, TPHA can be used for detecting anti-Treponema antibody,which has brown color. This can be also detected by the system of thepresent disclosure in the same or similar manner.

FIG. 19 illustrates an example table 700 of the first threshold 552 andthe second threshold 554. In this example, the first threshold 552 canbe at least one of a ratio of green component over red component 702, aratio of blue component over red component 704, a ratio of greencomponent over blue component 706, a difference between green and red708, a difference between blue and red 710, and a difference betweengreen and blue 712, In this example, the second threshold 554 isconsistent among different types of first threshold 552. In otherexamples, the second threshold 554 can vary by the type of firstthreshold 552.

FIG. 20 illustrates an example test result table 730 that shows adequatedispensation based on the first and second thresholds shown in FIG. 19 .In this example, nine tests are performed for different types of thefirst threshold 552. In this example, all of the numbers of pixels 732that exceeds the first threshold are smaller than the second threshold.Therefore, the dispensations are considered to be adequate.

FIG. 21 illustrates an example test result table 750 that showsinadequate dispensation based on the first and second thresholds shownin FIG. 19 , depending on different fluidic substances. In this table,some of the numbers 732 (shown highlighted in italic) exceed the secondthreshold, which indicates inadequate dispensation.

Although a detection of inadequate dispensation is primary described fora colored fluidic substance, it is also possible in other embodimentsthat a colorless fluidic substance can also be evaluated if it has beendispensed properly. In some examples, the system can detect one or morecolors resulting from different refraction indices of light passingthrough the surrounding portion 322 of the tray 108, as illustrated inFIG. 22 . In the FIG. 22 , the light path on the left side showsinadequate dispensation, and the light path on the right side showsadequate dispensation. As shown on the right side, the surroundingportion 322 remains substantially flat, and no refraction happens, whendispensation is adequate. However, when dispensation is inadequate, afluidic substance stays on the surrounding portion 322 and forms acurved boundary face to air. Since refraction index is varied withdifferent wavelength, different wavelengths of light refract differentlywhen the light passes through the fluidic substance on the surroundingportion 332 of the tray 108. Thus, colors can be detected in an image ofthe tray 108. By detecting such colors in the image resulting fromrefraction at the surrounding portion 332, dispensation of the fluidicsubstance on the tray 108 can be evaluated.

The various embodiments described above are provided by way ofillustration only and should not be construed to limit the claimsattached hereto. Those skilled in the art will readily recognize variousmodifications and changes that may be made without following the exampleembodiments and applications illustrated and described herein, andwithout departing from the true spirit and scope of the followingclaims.

What is claimed is:
 1. A method of evaluating dispensation of a fluidicsubstance on a tray in an automated analysis instrument, the methodcomprising: capturing, using an image capturing device, an image of atleast a portion of the tray, the portion of the tray comprising asurrounding portion disposed proximate to a receptacle comprised by thetray; obtaining color components of one or more fragments of the imageof at least the portion of the tray; and determining whether the fluidicsubstance is present on the surrounding portion comprised by the portionof the tray based on at least one of the color components of the one ormore fragments.
 2. The method of claim 1, further comprising: prior tocapturing the image of at least a portion of the tray, dispensing thefluidic substance on the receptacle comprised by the tray.
 3. The methodof claim 1, wherein the method comprises identifying, using at least onecomputing device, the surrounding portion comprised by the portion ofthe tray, and wherein identifying the surrounding portion includes:identifying a first image portion of the image, the first image portioncorresponding to the surrounding portion of the tray and including theone or more image fragments; and for each of the one or more imagefragments, obtaining a value associated with a color of the imagefragment; comparing the value with a first threshold; and designatingthe image fragment as a counted image fragment if the value of the imagefragment does not meet the first threshold.
 4. The method of claim 3,wherein determining whether the fluidic substance is present on thesurrounding portion includes: comparing a number of the counted imagefragments with a second threshold.
 5. The method of claim 4, furthercomprising: designating the at least a portion of the tray as a flaggedtray if the number of the counted image fragments does not meet thesecond threshold, the flagged tray representative of an inappropriatedispensation of the fluidic substance on the at least a portion of thetray.
 6. The method of claim 3, wherein the one or more image fragmentsincludes a plurality of pixels of the image of the at least a portion ofthe tray.
 7. The method of claim 3, wherein the value includes a ratiobetween a first color parameter and a second color parameter, the firstand second color parameters being different from each other andrepresentative of the color components of the image fragment.
 8. Themethod of claim 7, wherein the first and second color parameters areselected from red, green, and blue components of the image fragment. 9.The method of claim 3, wherein the value includes a difference between afirst color parameter and a second color parameter, the first and secondcolor parameters being different from each other and representative ofcolor components of the image fragment.
 10. The method of claim 1,wherein capturing an image of at least a portion of the tray includescapturing an image of the receptacle and no other receptacle comprisedby the tray.
 11. The method of claim 1, wherein capturing the image ofat least a portion of the tray includes: capturing an image of the tray;and dividing the image of the tray into a plurality of sub-images, eachsub-image including at least one receptacle portion and a surroundingportion around the at least one receptacle portion.
 12. The method ofclaim 3, wherein the first threshold is determined based on a type ofthe fluidic substance dispensed on the tray.
 13. The method of claim 1,wherein the tray includes a microplate having at least one well and atleast one surrounding surface around the at least one well.
 14. Themethod of claim 1, wherein the fluidic substance includes at least oneof a reaction reagent and a blood sample.
 15. A system for evaluatingdispensation of a fluidic substance dispensed in an automated analyzer,the system comprising: a tray including a plurality of receptacles and aplurality of surrounding portions around the plurality of receptacles; adispense device configured to dispense a fluidic substance on the tray;an image capturing device configured to capture at least one image of atleast a portion of the tray; at least one processing device; and atleast one computer readable storage medium storing software instructionsthat, when executed by the at least one processing device, cause thesystem to perform the method according to claim
 1. 16. A system forevaluating dispensation of a fluidic substance dispensed in an automatedanalyzer, the system comprising: a tray including a plurality ofreceptacles and a plurality of surrounding portions around the pluralityof receptacles; a dispense device configured to dispense a fluidicsubstance on the tray; an image capturing device configured to captureat least one image of at least a portion of the tray; at least oneprocessing device; and at least one computer readable storage mediumstoring software instructions that, when executed by the at least oneprocessing device, cause the system to perform the method according toclaim
 2. 17. A system for evaluating dispensation of a fluidic substancedispensed in an automated analyzer, the system comprising: a trayincluding a plurality of receptacles and a plurality of surroundingportions around the plurality of receptacles; a dispense deviceconfigured to dispense a fluidic substance on the tray; an imagecapturing device configured to capture at least one image of at least aportion of the tray; at least one processing device; and at least onecomputer readable storage medium storing software instructions that,when executed by the at least one processing device, cause the system toperform the method according to claim
 3. 18. A system for evaluatingdispensation of a fluidic substance dispensed in an automated analyzer,the system comprising: a tray including a plurality of receptacles and aplurality of surrounding portions around the plurality of receptacles; adispense device configured to dispense a fluidic substance on the tray;an image capturing device configured to capture at least one image of atleast a portion of the tray; at least one processing device; and atleast one computer readable storage medium storing software instructionsthat, when executed by the at least one processing device, cause thesystem to perform the method according to claim
 4. 19. A system forevaluating dispensation of a fluidic substance dispensed in an automatedanalyzer, the system comprising: a tray including a plurality ofreceptacles and a plurality of surrounding portions around the pluralityof receptacles; a dispense device configured to dispense a fluidicsubstance on the tray; an image capturing device configured to captureat least one image of at least a portion of the tray; at least oneprocessing device; and at least one computer readable storage mediumstoring software instructions that, when executed by the at least oneprocessing device, cause the system to perform the method according toclaim
 7. 20. A system for evaluating dispensation of a fluidic substancedispensed in an automated analyzer, the system comprising: a trayincluding a plurality of receptacles and a plurality of surroundingportions around the plurality of receptacles; a dispense deviceconfigured to dispense a fluidic substance on the tray; an imagecapturing device configured to capture at least one image of at least aportion of the tray; at least one processing device; and at least onecomputer readable storage medium storing software instructions that,when executed by the at least one processing device, cause the system toperform the method according to claim 11.